COGEU is a Specific Target Research Project (STREP) supported by the 7th Framework Programme, Contract number:

Transcription

1 COGEU is a Specific Target Research Project (STREP) supported by the 7th Framework Programme, Contract number:

2 Dr. Tim Forde Dr. Tim Forde

3 WHAT IS COGEU?

4 COGEU The COGEU project is a composite of technical, business, and regulatory/policy domains, with the objective of taking advantage of the TV digital switch-over (or analog switch-off) by developing cognitive radio systems that leverage the favourable propagation characteristics of the TVWS through the introduction and promotion of real-time secondary spectrum trading and the creation of new spectrum commons regime.

5 Motivation In Europe the complete digital switch over is planned for 2012 and will open a once in a lifetime opportunity for the networks of the future. Analog TV primary, PMSE secondary

6 Motivation In Europe the complete digital switch over is planned for 2012 and will open a once in a lifetime opportunity for the networks of the future. By switching from analogue to digital transmission more television channels can be broadcast using less spectrum. After analogue switch off the spectrum 790 MHz to 862 MHz (ch. 61 to 69), the so called digital dividend, will be/was entirely cleared from broadcast. DTV primary, PMSE secondary Future Mobile Communication (IMT) Digital Dividend

7 Motivation Within the remaining spectrum (470 MHz to 790 MHz) not all channels are occupied at each location. These locally unused channels are referred to as TV White Spaces (TVWS). How do we transform the TV White Spaces into social benefits and economic growth? DTV primary, PMSE secondary Future Mobile Communication (IMT) Digital Dividend

8 Motivation

9 Motivation TVWS are quite stable because terrestrial broadcasting is planned around relatively inflexible high power high tower distribution networks. Strong interest by mobile cellular network operators to use lower frequencies, as network rollouts costs are dramatically lower 2 GHz coverage 700 MHz coverage

10 COGEU domains Regulation domain Economic domain Technology domain

11 COGEU consortium

12 AND AT THE THE END?

13 Final COGEU demo

14 TVWS database Final COGEU demo 1

15 Ch. 58 TVWS geo-location database

16 Ch. 59 TVWS geo-location database

17 TVWS geo-location database

18 policies Final COGEU demo 2

19 assignment Final COGEU demo 3

20 transceiver Final COGEU demo 4

21 TVWS transceiver COGEU Data Link DVB-T Sensor Slave WSD GPS Sensor Master WSD 8 MHz assignment creating a node-to-node link in TVWS

22 COGEU TVWS Transceiver = Software-based Cognitive Radio: IRIS / Labview RF-frontend for Interleaved TV spectrum Data I/O Baseband Signal Processing Upconversion/ Interpolation Downconversion/ Decimation ADC DAC USRP DB USRP DB IRIS/Labview Driver USRP

23 WHAT WAS THE QUESTION?

24 FIRE What is a good experiment? How can an experiment can be unambiguously defined? What output do we expect from an experiment? How do we control the wireless environment?

25 FIRE What is a good experiment? How can an experiment can be unambiguously defined? What output do we expect from an experiment? How do we control the wireless environment?

26 FIRE A good experiment should help with the evaluation, validation, demonstration of an idea. A good experiment should be rigorously described so that it is repeatable and results should be reproducible

27 But is that enough? FIRE

28 FIRE But is that enough? How is your work/output measured?

29 FIRE But is that enough? How is your work/output measured? Demos are nice, but will they be remembered?

30 FIRE But is that enough? How is your work/output measured? Demos are nice, but will they be remembered? Publications Publications Publications

31 FIRE But is that enough? How is your work/output measured? Demos are nice, but will they be remembered? Publications Publications Publications 5 page conference papers + rigorous description of a wireless experiment: are they compatible?

32 FIRE What is a good experiment? How can an experiment can be unambiguously defined? What output do we expect from an experiment? How do we control the wireless environment?

33 With great difficulty. FIRE

34 FIRE With great difficulty. Defining the things being evaluated. Moving from paper Matlab to a cognitive radio implementation.

35 FIRE With great difficulty. Defining the things being evaluated. Moving from paper Matlab to a cognitive radio implementation. Defining the objectives, constraints. In COGEU much ambiguity has been removed as the application area is very defined: Frequencies are known Primary/incumbent neighbours are known Some policy objectives are known

36 FIRE What is a good experiment? How can an experiment can be unambiguously defined? What output do we expect from an experiment? How do we control the wireless environment?

37 FIRE That depends. What stage are we at? Prototype Development Validation and Demonstration Certification

38 PROTOTYPING

39 COGEU TVWS Transceiver COGEU TVWS transceiver is part of a larger system DVB-T PMSE TVWS Occupancy Repository COGEU BROKER Dynamic TVWS allocation mechanism Policies Repository GEOLOCATION SPECTRUM DATABASE Trading Information Repository Trading mechanism and Price discovery Payment System GUI Performance Monitor Registration and Validation Broker Interface Negotiation protocol for spectrum trading Software-based Cognitive Radio: IRIS Radio & Labview RF-frontend for Interleaved TV spectrum External Control Information Access Player A (spectrum buyer) (WP5) Player A (TVWS-Transceiver) (WP5) Other players emulated by software

40 FIRE What is a good experiment? How an experiment can be unambiguously defined? What output do we expect from an experiment? How do we control the wireless environment?

41 What do we expect this system to do? GEOLOCATION SPECTRUM DATABASE GPS Sensor Master WSD 1

42 2 GEOLOCATION SPECTRUM DATABASE DVB-T Master WSD 8 MHz assignment

43 GEOLOCATION SPECTRUM DATABASE 3 COGEU Data Link DVB-T Sensor Slave WSD GPS Sensor Master WSD 8 MHz assignment

44 GEOLOCATION SPECTRUM DATABASE COGEU Data Link DVB-T Sensor Slave WSD 4 8 MHz assignment GPS Sensor Master WSD

45 TVWS transceiver components Sensing Rendezvous Geo-location Shaping

46 What do we expect these components/algorithms to do?

47 What do we expect these components/algorithms to do? Phase Signal Generation Signal Transmission &Channel Signal Analysis 1 MATLAB MATLAB channel models MATLAB

48 From paper to prototype Phase Signal Generation Signal Transmission &Channel Signal Analysis 1 MATLAB MATLAB channel models MATLAB 2 MATLAB Signal Generator USRP MATLAB

49 From paper to prototype Phase Signal Generation Signal Transmission &Channel Signal Analysis 1 MATLAB MATLAB channel models MATLAB 2 MATLAB Signal Generator USRP MATLAB 3 MATLAB Signal Generator USRP Iris

50 From paper to prototype Phase Signal Generation Signal Transmission &Channel Signal Analysis 1 MATLAB MATLAB channel models MATLAB 2 MATLAB Signal Generator USRP MATLAB 3 MATLAB Signal Generator USRP Iris 4 Iris Direct Connection Iris

51 From paper to prototype Phase Signal Generation Signal Transmission &Channel Signal Analysis 1 MATLAB MATLAB channel models MATLAB 2 MATLAB Signal Generator USRP MATLAB 3 MATLAB Signal Generator USRP Iris 4 Iris Direct Connection Iris 5 Iris Iris AWGN Channel Iris

52 From paper to prototype Phase Signal Generation Signal Transmission &Channel Signal Analysis 1 MATLAB MATLAB channel models MATLAB 2 MATLAB Signal Generator USRP MATLAB 3 MATLAB Signal Generator USRP Iris 4 Iris Direct Connection Iris 5 Iris Iris AWGN Channel Iris 6 Iris USRP -> USRP Iris

53 SHAPING

54 Transmit shaping DVB-T 8 MHz assignment

55 OFDM-based shaping techniques were investigated to enable: Efficient use of available spectrum Protection of incumbent users, i.e. DVB-T, PMSE users Cancellation Carriers Windowing Transmit Shaping

56 Normalized PSD (db) OFDM-based shaping techniques were investigated to enable: Efficient use of available spectrum Protection of incumbent users, i.e. DVB-T, PMSE users Cancellation Carriers Windowing Transmit Shaping CCs per edge windows (Length: 32) windows (Length: 16) & 2 CCs per edge subcarrier index Comparison of CCs method, windowing and combination of both methods

57 OFDM-based shaping techniques were investigated to enable: Efficient use of available spectrum Protection of incumbent users, i.e. DVB-T, PMSE users Cancellation Carriers Windowing Transmit Shaping

58 Map to subcarriers QAM Modulation Apply Cancellation carriers IFFT Transmit Shaping Implementation in C++ in the IRIS SDR. Configurable OFDMbased modulator and demodulator components with inbuilt CC & Windowing Data for this symbol Cyclic Extension OFDM Symbol Creation Steps Add windowing extension Incorporate into frame frequency domain time domain

59 Transmit Shaping Implementation in C++ in the IRIS SDR. Configurable OFDMbased modulator and demodulator components with inbuilt CC & Windowing

60 Implementation in C++ in the IRIS SDR. Configurable OFDMbased modulator and demodulator components with inbuilt CC & Windowing Kick-started implementation with Dublin week-long workshop. Uses LPACK Fortran linear programming library Transmit Shaping

61 RENDEZVOUS

62 Rendezvous in a Dynamic Spectrum Access (DSA) context refers to the ability of two or more radios to meet and establish a link on a common channel. Embedded cyclostationary signatures. Rendezvous

63 Rendezvous Rendezvous in a Dynamic Spectrum Access (DSA) context refers to the ability of two or more radios to meet and establish a link on a common channel. Embedded cyclostationary signatures.

64 Rendezvous in a Dynamic Spectrum Access (DSA) context refers to the ability of two or more radios to meet and establish a link on a common channel. Embedded cyclostationary signatures. Rendezvous

65 Rendezvous

66 Performance Evaluation Rendezvous Matlab-based simulations Exponential Decay and Bad Urban (Cost 207) channel models Flat-fading, frequency-selective fading, fast-fading (Jakes s Doppler both at high frequency and at TVWS frequency) 4Mhz signals using subcarrier spacing of 3GPP LTE Key Metrics Time-to-rendezvous Ability to detect Ability to identify Ability to acquire frequency

67 Rendezvous: Detection No. of features Redundant Carriers Overhead Average P d (over all speeds) for P fa =0, t = 30 2 x (M=2) % 62% 2 x (M=3) % 88% 3x(M=3) % 97% (94% at t = 20 ) Exponential Decay Model

68 Rendezvous: Identification Signature Identification finding the signal of interest Fast-fading Jakes Doppler, Bad Urban Carrier freq. 630MHz Max. Doppler shifts 25km/h-75km/h 3-feature cyclo-signatures 4MHz signal with 3GPP LTE subcarrier spacing

69 Rendezvous: Frequency Acquisition Frequency Acquisition can be used when there is no prior knowledge as to what a signature means in terms of centre frequency. 8MHz band of interest Signal of interest occupies 20% of band

70 Rendezvous: Frequency Acquisition 8MHz band of interest Signal of interest occupies 20% of band P acq > 95% for SNR >6dB P acq > 99.9% for SNR >12dB

71 Experimentation beyond Matlab Extensive experimentation in Matlab Especially challenging for mobile scenarios Reduced set implemented in Iris SDR Very reduced set of conditions evaluated in reality No mobile to date Hard (expensive?) to create challenging test environment.

72 Repeatable System Experimentation Evaluation with mature transceiver: Spectrum efficiency Packet error rates TTR, Detection, Identification, Frequency Acquisition With and without the USRPs

73 COMPONENTS TO SYSTEM

74 Experimenting with a system Sensing Rendezvous Geo-location Shaping

75

76 Integration and Experimentation Integration is not trivial. Components go through exhaustive individual development System integration takes a somewhat big-bang approach Some system behaviour can not be anticipated Workshops are crucial when development teams are remote.

77 Integration and Experimentation USRP transmitter Database access LabVIEW/ IRIS USRP Sensing Cogeu TVWS Tranceiver

78 What did we learn? The ideal Matlab transceiver is not real. The real USRP/Iris transceiver is not ideal. Moving towards reality for experimentation curtails the parameter space: Constrained effective bandwidths Constrained transmit power Constrained host processing capabilities Limits the graphibility of real-world experiments

79 And about experimentation? Repetition of performance is hard. Why? Surmountable reasons: wrong versions of code, USRP drivers, etc. Flakey reasons: changing hardware, inconsistent hardware. Insurmountable reasons: the wireless environment.

80 MORE DEMOS

81

82 Aalborg Validation sites Banska Bystrica

83 TVWS BS Munich

84 Banska Bystrica Banska Bystrica is a extremely broken and mountainous region in the middle of Slovakia with high dense populated areas. Its average distance of 100 km from borders and geographical conditions (surrounded by hills) makes the existence of unused TV channels highly probable, and a good case study for COGEU rural broadband scenario.

85 FIRE What is a good experiment? How an experiment can be unambiguously defined? What output do we expect from an experiment? How do we control the wireless environment?

86 Test & Trial Clean spectrum. 2.4GHz dirty and noisy. 5GHz less so. Other bands. generally illegal Publication of results from illegal experimentation may be problematic.

87 Clean Spectrum

88 CTVR Test & Trial 25 MHz 25 MHz Transmit Sites 2.08 GHz 2.35 GHz

89 IEEE DySPAN 2007 Dublin Channel Centre Freq. (MHz) Max ERP BW (MHz) Mobile W (0dBW) 1.75 Yes W (0dBW) 1.75 Yes W (0dBW) 1.75 Yes W (0dBW) 1.75 Yes W (0dBW) 1.75 Yes W (0dBW) 1.75 Yes W (10dBW) 1.75 Yes W (0dBW) 1.75 Yes W (10dBW) 1.75 Yes W (0dBW) 1.75 Yes W (0dBW) 50.0 No W (0dBW) 50.0 No DARPA XG Node Qinetiq Radios

90 Test & Trial NOWHERE or 90km from SOMEWHERE

91 Conclusions What is a good experiment? How an experiment can be unambiguously defined? What output do we expect from an experiment? How do we control the wireless environment?

92 Dr. Tim Forde Questions